The Role :-

We are looking for a hands-on Data Engineer to join our growing team. You should be a GCP-native engineer, deeply proficient in the Google Cloud tooling stack, owning the design, build, and optimisation of data pipelines that bring data from a range of source systems into GCP to feed critical AI and analytics workflows. This is a deeply technical role. You will be expected to get hands-on from day one.

What You Will Do
Design and implement scalable data ingestion pipelines from a variety of systems including on-premise, Azure Databricks and c3.ai
Build and maintain Bronze-to-Silver transformation pipelines following the Medallion architecture, using a config-driven approach
Optimise BigQuery data organisation through effective partitioning, clustering, and schema design for large-scale, high-performance querying
Implement and maintain workload identity federation and APIM integrations for secure cross-platform data movement
Collaborate with Data Governance teams to embed data quality checks within various layer transformations, targeting defined quality thresholds
Contribute to pipeline design reviews and actively participate in medallion architecture planning sessions with platform and architecture teams
Document data flows, transformation rules,



and design decisions to support knowledge transfer and team continuity

Must-have skills
Hands-on data engineering experience
Robust GCP expertise: BigQuery (partitioning, clustering, optimisation), GCS, Dataflow or equivalent
Proven experience designing and building ETL/ELT pipelines at scale
Experience with Medallion architecture (Bronze / Silver / Gold layers)
Data integration experience across heterogeneous sources on-premise databases, APIs, cloud platforms
Proficiency in Python and/or SQL for pipeline development
Experience with config-driven pipeline design and parameterised frameworks Solid advantage
Experience with cross-cloud data movement (eg Azure GCP)
Familiarity with APIM, workload identity federation, or service account impersonation patterns

How You Will Work
Embedded with the client's platform and architecture team in an agile delivery model
Close collaboration with Data Governance, EA, and AI platform teams
Expected to operate independently on technical tasks while contributing to broader design discussions
Resource substitutions are permitted but subject to prior review and approval by the client team

📌 Data Engineer Gurugram
🏢 Talent Monitor Bangalore
📍 Gurugram